code: def test_cv_scores(cv, est, verbose, X):
      scores = cross_val_score(
          est,
          y,
          X=X,
          scoring="mean_squared_error",
          cv=cv,
          verbose=verbose,
      )
      assert isinstance(scores, np.ndarray)
  
file_path: pmdarima/pmdarima/model_selection/tests/test_validation.py
imports: from pmdarima.arima import ARIMA
  from pmdarima.warnings import ModelFitWarning
  from pmdarima.compat.pytest import pytest_error_str
  from pmdarima.pipeline import Pipeline
  from pmdarima.preprocessing import FourierFeaturizer
  from pmdarima.model_selection._split import RollingForecastCV, SlidingWindowForecastCV
  from pmdarima.model_selection._validation import cross_val_score, _check_scoring, cross_validate, cross_val_predict, _check_averaging
  from pmdarima.datasets import load_airpassengers
  import pytest
  import numpy
  from unittest import mock
label_desc: Use image node_id 1 for calling a global function with example usage: test_cv_scores(cv, est, verbose, X) without return types